1. Field
This disclosure generally relates to the field of image capture systems. More particularly, the disclosure relates to camera calibration.
2. General Background
Camera calibration is currently utilized in a variety of areas to find the correspondence of a real world coordinate system with a coordinate system of a camera. Camera calibration is often utilized to calibrate projector-camera systems. Further, camera calibration is often utilized to calibrate multi-camera systems that track people and their interactions.
Current approaches to calibrating one or more cameras utilize a checkerboard target, a distinctive point such as a light emitting diode (“LED”) light source that is moved from position to position, or multiple naturally occurring points in a scene. In the approach that utilizes the checkerboard target, the one or more cameras are typically directed toward the checkerboard target that is typically held by a human. The calibration involves the human adjusting the checkerboard to be located at different ranges from the camera with different inclinations. In the approach that utilizes a moving distinctive point, the one or more cameras are typically directed toward the distinctive point that is typically held by a human. The calibration involves the human moving the distinctive point through a variety of positions. With respect to the approach that utilizes multiple naturally occurring points in a scene, the multiple naturally occurring points must have an appropriate distribution in the scene. Otherwise, the calibration will not be correct, e.g., the calibration will not be correct if the naturally occurring points lie on a line or a plane.
The approaches with the checkerboard and the moving distinctive point often have unskilled workers performing the tasks incorrectly. Uncertainty and wasted time often result. If the human does not perform the calibration task correctly, the calibration approaches do not provide helpful diagnostic messages that aid the user in performing the calibration task correctly.
Further, the current calibration approaches do not fully specify the real world coordinate system because they do not specify the position of the origin of the real world coordinate system or the orientation of the axes of the real world coordinate system. An additional step is necessary to fully specify the real world coordinate system, which typically involves a human providing a manual input for the camera images. This additional step requires extra work and is often a source of error.
In addition, the current calibration approaches do not specify scene information such as the location of the ground plane in the world coordinate frame. An additional step is necessary to specify such information, which typically involves a human providing a manual input for the camera images. This additional step also requires extra work and is often a source of error.
It is believed that improvements are needed to provide better diagnostics for camera calibration and to provide a better methodology to specify the origin of the world coordinate frame and the orientation of the axes. It is also believed that improvements are needed to provide a better methodology to specify scene information such as the location of the ground plane.